HealthMap: Global Infectious Disease Monitoring through Automated Classification and Visualization of Internet Media Reports

Freifeld, Clark C.; Mandl, Kenneth D.; Reis, Ben Y.; Brownstein, John S.

doi:10.1197/jamia.m2544

Cited by 394 publications

(335 citation statements)

References 20 publications

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“…HealthMap provides a comprehensive view of the current global state of infectious diseases by bringing together disparate data sources [28]. Health GeoJunction extracts textual information from scientific literature, PH reports, and news reports to support the discovery of relationships between documents [29].…”

Section: Visualizations For Health Literacymentioning

confidence: 99%

Health Literacy for the General Public: Making a Case for Non-Trivial Visualizations

Ola

Sedig

2017

Informatics

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Health literacy is concerned with the degree to which individuals can access and understand information to make health decisions. The multifaceted nature of health data presents challenges for individuals seeking to improve their understanding of health. To aid health literacy efforts, we have developed HealthConfection, a visualization tool that uses elaborate and non-typical interactive visualizations to represent health data. In this paper, we report on two studies we conducted with HealthConfection. In the first study, we investigate whether individuals can learn to use non-typical visualizations, and the impact that short, minimalist video tutorials will have on participants' understanding of the visualizations. The findings from this study suggest that individuals can learn to use non-typical visualizations and that participants who used the tutorials achieved higher scores than those without tutorials. This work indicates that non-typical visualizations are a viable option for conveying complex datasets. Based on this foundation, we conducted a second study to investigate if non-typical visualizations can improve health literacy for the general public. Results show that participants who used HealthConfection achieved higher scores than those who did not interact with the tool. Our work suggests that non-typical visualizations can be used to improve health literacy.

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Section: Visualizations For Health Literacymentioning

confidence: 99%

Health Literacy for the General Public: Making a Case for Non-Trivial Visualizations

Ola

Sedig

2017

Informatics

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“…healthmap.org/en/an), an open access online infectious disease outbreak monitoring system (9,10). HealthMap integrates outbreak-related data from >30,000 electronic sources, including the news media, ProMED-mail, and other electronic public health reporting sources, by using algorithms to classify the diseases and locations associated with each report.…”

Section: The Studymentioning

confidence: 99%

Electronic Event–based Surveillance for Monitoring Dengue, Latin America

Hoen¹,

Keller²,

Verma³

et al. 2012

Emerg. Infect. Dis.

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“…While no doubt germane to the swine-flu outbreak, it is moot if the publication of the article should be considered as a reflection of public interest in the outbreak. Details of how online reports are collected and categorized by HM are in [26].…”

Section: Introductionmentioning

confidence: 99%

Nowcasting influenza outbreaks using open-source media report.

Ray¹,

Brownstein

2013

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We construct and verify a statistical method to nowcast influenza activity from a time-series of the frequency of reports concerning influenza related topics. Such reports are published electronically by both public health organizations as well as newspapers/media sources, and thus can be harvested easily via web crawlers. Since media reports are timely, whereas reports from public health organization are delayed by at least two weeks, using timely, open-source data to compensate for the lag in "official" reports can be useful. We use morbidity data from networks of sentinel physicians (both the Center of Disease Control's ILINet and France's Sentinelles network) as the gold standard of influenza-like illness (ILI) activity. The time-series of media reports is obtained from HealthMap (http://healthmap.org). We find that the time-series of media reports shows some correlation (≈ 0.5) with ILI activity; further, this can be leveraged into an autoregressive moving average model with exogenous inputs (ARMAX model) to nowcast ILI activity. We find that the ARMAX models have more predictive skill compared to autoregressive (AR) models fitted to ILI data i.e., it is possible to exploit the information content in the open-source data. We also find that when the open-source data are non-informative, the ARMAX models reproduce the performance of AR models. The statistical models are tested on data from the 2009 swine-flu outbreak as well as the mild 2011-2012 influenza season in the U.S.A.

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HealthMap: Global Infectious Disease Monitoring through Automated Classification and Visualization of Internet Media Reports

Abstract: HealthMap is a useful free and open resource employing text-processing algorithms to identify important disease outbreak information through a user-friendly interface.

Cited by 394 publications

References 20 publications

Health Literacy for the General Public: Making a Case for Non-Trivial Visualizations

Health Literacy for the General Public: Making a Case for Non-Trivial Visualizations

Electronic Event–based Surveillance for Monitoring Dengue, Latin America

Nowcasting influenza outbreaks using open-source media report.

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